Researchers have developed a new imaging method that rapidly predicts how cancer drugs will work in patient-derived tumor models. Patient-derived cancer organoids (PDCOs) are 3D models grown from a patient’s tumor, providing a realistic way to study treatment response, but current tests often miss resistant cells and early changes.
The technique, Wide-Field Optical Redox Imaging (WF ORI), measures natural fluorescence from metabolic molecules such as NAD(P)H and FAD to calculate the Optical Redox Ratio, which reflects early metabolic shifts before tumors shrink or cells die. Using standard wide-field microscopes, WF ORI can detect differences within organoids, including resistant cells, and a “leading-edge detection” approach focuses on the outermost, most active layer of the tumor models, making it highly sensitive to drug effects.
WF ORI also distinguishes organoids with different genetic mutations. Colorectal cancer organoids with KRAS and PIK3CA mutations showed distinct signals from wild-type organoids. A machine-learning model could accurately identify resistant mutant cells in mixed cultures. The method detected differential responses to drugs like panitumumab more clearly than standard size-based measures. WF ORI is a fast, cost-effective, and sensitive tool that could improve precision cancer therapy by identifying early responses and resistant cell populations.